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https://huggingface.co › transformers › model_doc › auto.html
Instantiating one of AutoModel AutoConfig and AutoTokenizer will directly create a class of the relevant architecture ex model

https://huggingface.co › transformers › preprocessing.html
If you plan on using a pretrained model it s important to use the associated pretrained tokenizer it will split the text you give it in

https://deepwiki.com › huggingface › course
The AutoTokenizer class works similarly to AutoModel automatically selecting the appropriate tokenizer class for a

https://stackoverflow.com › questions
I happened to want the uncased model but these steps should be similar for your cased version Also note that my

https://github.com › huggingface › transformers › issues
While loading pretrained BERT model what s the difference between AutoTokenizer from pretrained and

https://github.com › huggingface › transformers › issues
We always supply the config as we use this code for multiple models in transformers as well as our custom models

https://www.codegenes.net › blog › pytorch-autotokenizer
The most common way to use AutoTokenizer is to load a pre trained tokenizer using the from pretrained method

https://stackoverflow.com › questions
I obtained a pre trained BERT and respective tokenizer from HuggingFace s transformers in the following way The

https://colab.research.google.com › github › hugging...
If you plan on using a pretrained model it s important to use the associated pretrained tokenizer This ensures the text is split the